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Using mobile crowdsourcing data to retrieve the location-aware information
PhD Thesis Proposal Defence
Title: "Using mobile crowdsourcing data to retrieve the location-aware
information"
by
Mr. Xiaonan GUO
ABSTRACT:
Location-based services (LBS) can benefit from location information and indoor
maps Recent research focuses on how to use sensor reading from smart phone to
automatically reconstruct the walking pathway and floor plan. However, existing
approaches have two limitations. On the one hand, the floor the room boundaries
detection algorithm used in previous work may regard counter, shelf or
obstacles as wall. On the other hand, having outline information may not be
very useful to the commercial expense activities, such as advertising, shopping
and dining. In this proposal, we aim to design a system that makes use of
dynamic crowdsourcing data from smart phone to accurately construct the floor
plan of shopping malls and label shop with types and brand name. Our empirical
experiments show that people moving pattern and acoustic information are varied
from different shops. Moreover, due to the pervasive WiFi, nearly all the shops
have APs to provide wireless connections either for customers or their own
employee and they are more likely to use the brand name as SSID. By
investigating these observations, we design a novel gradient based algorithm in
shops boundaries detection. Then we leverage people moving pattern and acoustic
information obtained from smart phone to classify shops into different types.
Finally, we generate a WiFi heat map from crowdsourcing data and matching APs
in the floor plan to pinpoint shop location and use SSID to indicate brand
name. We only leverage mobile phone sensor reading without human intrusion.
Date: Wednesday, 8 May 2013
Time: 1:00pm - 3:00pm
Venue: Room 3405
lifts 17/18
Committee Members: Prof. Lionel Ni (Supervisor)
Dr. Huamin Qu (Chairperson)
Dr. Lei Chen
Dr. Qiong Luo
**** ALL are Welcome ****